Modelling real‐world effects in near‐field SAR collections for compressive sensing

Abstract The ability to control sidelobes in a SAR image is critical to forming images that are useful for interpretation and exploitation. QinetiQ has developed the RIBI sensing system, which utilises a distributed coherent array of sensors to produce multistatic images. These systems require techniques from outside the traditional radar domain to utilise the theoretical resolution possible in synthesising a coherent aperture from multiple disparate collections. This paper develops previously published work on using compressive sensing techniques to suppress sidelobes in SAR images to develop a higher‐fidelity measurement model. Using Cranfield University's GBSAR System a series, experimental measurements are conducted, and image estimation techniques are applied to this real data. It demonstrates an improvement in recovery performance over an isotropic measurement matrix, and discusses areas which require further development.

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Publication Details

Journal
IET Radar Sonar & Navigation
Published
2025-01-01
DOI
https://doi.org/10.1049/rsn2.12692
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Modelling real‐world effects in near‐field SAR collections for compressive sensing

Daniel André, Peter Yuen, Chris Moate, George A. J. Price et al.
IET Radar Sonar & Navigation
Sparse and Compressive Sensing Techniques
article

Modelling real‐world effects in near‐field SAR collections for compressive sensing

Daniel André, Peter Yuen, Chris Moate, George A. J. Price, Mark Finnis
article en

Abstract

Abstract The ability to control sidelobes in a SAR image is critical to forming images that are useful for interpretation and exploitation. QinetiQ has developed the RIBI sensing system, which utilises a distributed coherent array of sensors to produce multistatic images. These systems require techniques from outside the traditional radar domain to utilise the theoretical resolution possible in synthesising a coherent aperture from multiple disparate collections. This paper develops previously published work on using compressive sensing techniques to suppress sidelobes in SAR images to develop a higher‐fidelity measurement model. Using Cranfield University's GBSAR System a series, experimental measurements are conducted, and image estimation techniques are applied to this real data. It demonstrates an improvement in recovery performance over an isotropic measurement matrix, and discusses areas which require further development.

IET Radar Sonar & NavigationVol. 19(1)
Qinetiq (United Kingdom) (GB), Cranfield University (GB), Defence Academy of the United Kingdom (GB)
QinetiQ
Openalex Percentile: Top 99%
Sparse and Compressive Sensing Techniques
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